Graphene is a two dimensional material comprising a single layer of carbon atoms arranged in a honeycomb grid. It has many advantageous room temperature properties like almost twice the electrical conductivity of copper, more than ten times the thermal conductivity of silver, almost thirty times the electron mobility of silicon, about 5 times the tensile or Young's modulus of steel, and more than 45 times the tensile strength of diamond.
These properties enable many uses and improvements when using graphene.
High quality graphene may e.g. be obtained by a technique usually referred to as micro-cleaving or micro-mechanically cleaving or various exfoliation methods.
Alternatively, graphene can be ‘grown’ using chemical vapour deposition (CVD) methods. However, a drawback of CVD is that graphene typically is ‘grown’ on copper or nickel and then need to be moved to another usable substrate using a so-called transfer technique. Furthermore, each coherent area of graphene obtained in this way is relatively small, i.e. CVD graphene can be seen as comprising a larger number of much smaller adjacent graphene areas.
Graphene has a thickness of only 0.335 nm whereby characterization tools involving equipment such as atomic force microscope (AFM), scanning tunneling microscope (STM), or scanning electron microscope (SEM) often is used to properly and reliably identify graphene. However, using these techniques is time consuming and the equipment is also relatively costly.
Furthermore, given that coverage of research or similar grade single-layer micro-cleaved graphene is typically only some few thousand μm2 on a 4″ wafer or similar, such time consuming identification methods are not practical for large-scale production or research use.
Alternatively, manual identification of graphene—which is still used—is slow, tedious and/or error-prone, especially for fragmented samples. Typical time spent on manual identification of graphene is e.g. about 5 seconds pr. digital image and about 6-7 hours for a 4″ wafer when digitised at an appropriate resolution needed to properly identify graphene.
Patent application US 2011/0299720 discloses to an automated approach for determining a number of atomic planes in layered material samples. According to one aspect, calibration is carried out for a thin film material under specific illumination conditions where a correlation is determined between the number of layers of the layered thin film material and a range of colour component values. The correlation is then used to determine the number of layers in a selected region of an image for another sample comprising the same material as used during the calibration. For accurate results, the image needs to be captured under the same illumination conditions as used during the calibration.
Calibration is carried out e.g. using micro-Raman spectroscopy and atomic force microscopy (AFM).
Once the calibration is carried out, it may be used for layer detection for other samples as long as the sample material and the calibration material is the same, the substrate for the calibration material and for the sample material is the same, and the illumination conditions stay the same.
However, it is not practically simple ensuring that illumination conditions truly stay the same and a given sample material will always have small variations e.g. in thickness, even across the sample material.
Thus, there is a need for an automated simple, reliable, robust, and/or efficient way of identifying graphene and/or other thin-film materials in a digital image.